“They're not just fire pits, they're Sacred Fires”: Traditional healing spaces as sites of anticolonial resistance in a Toronto hospital
Bibliographic record
Abstract
Globally, there is a movement to revive ancient Indigenous practices of traditional healing (TH) that utilize Land-based medicine and emphasize a wholistic approach to wellness. In Canada, the Truth and Reconciliation Commission's Call to Action urges the integration of Indigenous TH practices into healthcare systems. Drawing from anticolonial theory and Indigenous health geographies, this research examines traditional healing spaces (TH spaces) at the Centre for Addiction and Mental Health (CAMH) as an in-depth case study to understand how TH spaces transform institutional 'space' into Indigenous 'place' while challenging dominant biomedical paradigms. Using an Indigenous community-engaged methodology and qualitative interviews with Indigenous and allied health care staff at CAMH (n = 22), this study analyzes how TH spaces function as sites of both healing and resistance across multiple scales - individual, institutional, and societal. The research compares perspectives between staff groups to understand the roles, responsibilities, and meanings of TH spaces within the complex dynamics of healthcare reconciliation, while centering Indigenous self-determination in these transformative processes. Key findings indicate that transformation of space for TH must privilege Indigenous self-determination and that Indigenous and wholistic cultural practices benefit from conditions that connect to the natural environment. Nurturing relationships and valuing Indigenous knowledge is essential for the uptake of TH within colonial and institutional frameworks, and this case underscores the need for significant commitment by those in power to affect structural change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.048 | 0.048 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".